In addition to the classification loss, we employ an auxiliary loss that encourages support features from different classes to span the latent space [1]}:
\(L_{\rm aux} = \sum _{i\in C} \sum _{j\in C, j\ne i} ||\hat{S}_i \hat{S}_j^T||^2\) 
